Estimation of Bayesian Item Response Models

  • Jean-Paul Fox
Part of the Statistics for Social and Behavioral Sciences book series (SSBS)


The general form of a Bayesian item response model consists of a probability model for the responses, prior distributions for the model parameters, and possibly prior distributions for the hyperparameters. An overview of Bayesian procedures for simultaneous estimation is given in which MCMC estimation methods are emphasized. Interest is focused on simultaneous estimation of marginal posterior densities of item and person parameters.


Item Parameter European Social Survey Augmented Data Discrimination Parameter Item Response Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer New York 2010

Authors and Affiliations

  • Jean-Paul Fox
    • 1
  1. 1.Department of Research Methodology, Measurement, and Data Analysis Faculty of Behavioral SciencesUniversity of TwenteEnschedeThe Netherlands

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